The identity of the self-antigens that drive pathogenic CD4+ T cell responses remains largely unknown, especially in the context of systemic autoimmune diseases, such as systemic lupus erythematosus. Even in many tissue-specific autoimmune diseases, e.g. rheumatoid arthritis, it is often not clear which self-antigens are being targeted. Furthermore, in all but a few experimental systems, we do not know what the consequences of antigen recognition are for autoreactive CD4+ T cells, particularly on the cellular and molecular level, and how this might be affected by genetic factors. In this project, we will use synthetic peptide combinatorial libraries, arranged in a positional scanning format, to identify the ligands for autoreactive CD4+ T cells found in experimental mouse models of systemic and tissue-directed autoimmune disease. We will also use a novel, retrovirus-based technique to study the fate of these autoreactive cells when they encounter their self-antigens in different genetic backgrounds. Our ultimate goal is to combine these two approaches to define how specific genes, or gene polymorphisms, that affect susceptibility to autoimmune disease, control the fate of autoreactive T cells as they respond to defined self-antigens. By addressing these questions we should gain important insights into how self-tolerance is established and maintained. These may suggest novel approaches to prevent or cure autoimmune diseases.